AI's Insatiable Appetite For Silicon Requires New Chips

One breakthrough of AI is deep learning: a branch of machine learning that can uncannily identify objects in images, recognize voices, and create other predictive models by analyzing data. Deep learning can use regular CPUs, but for serious projects, data science and AI engineering teams must use AI chips such as GPUs that can handle massively parallel workloads to more quickly train and continuously retrain models on large data sets. And, it's why all the internet giants, including Amazon, Facebook, Google, and Microsoft, have massive investments in AI infrastructure. Integrated circuits, computer systems, and/or cloud services that are designed to optimize the performance of AI workloads, such as deep learning model training and inferencing. When it comes to AI deep learning, GPUs get all the press.